nwfscDiscard.RmdThe nwfscDiscard package was written by scientists at the Northwest Fisheries Science Center (NWFSC) to explore and process West Coast Groundfish Observer Program (WCGOP) data. This package can be used to process WCGOP data for West Coast groundfish assessments.
nwfscDiscard can be used to:
Ensure confidentiality is met based on the requested stratification of data by gear and area.
Summarize observed discard rates by gear and area for catch share and non- catch share vessels.
Summarize biological data from observed discards for use in groundfish stock assessments.
Visualize data.
The code combines the data into fleet structures requested by users based on gear and areas. The gear and area grouping are passed to all of the processing functions:
# Gears to keep and how they should be grouped within a list:
gear_groups <- list(c("Bottom Trawl", "Midwater Trawl", "Shrimp Trawl"), c("Hook & Line", "Pot"))
gear_names <- c("trawl", "fixed gear")
# Fleet areas:
fleet_groups <- list(c("WA", "OR", "CA"))
fleet_names <- c("coastwide")where the above code groups the data into two coastwide fleets based upon gear types. The data can be grouped by state or by latitude. The WCGOP data contains both a departure and return states. Generally, the return state is used to group data based on state areas. If the data area being grouped by latitude this can be done by using the latitude of the set (SET_LAT), the average latitude across a set (AVG_LAT), or by the latitude that the gear was retreived (UP_LAT). If the data needs to be split north and south of 40 10 N. latitude, the WCGOP data contains a field that specifies north or south based on the average latitude (AREA). Since the data can be split across various fields (state or latitude) the column name to specify the grouping needs to be specified:
fleet_colname = "r_state"where the above example groups the data based on the return state. The fleet column name should be a column in the data.
Currently, there are a couple of functions that provide summaries and plots of the data to help users. The first is a function that pull data from the GEMM which has expanded catches based on the retained and discard observations by WCGOP. The catch by sector is then summarized by sectors that are catch shares or non-catch shares. This information could be used to better inform how the rates between the groups could be combined for use in an assessment (e.g., are the majority of catches occurring by catch share vessels?).
gemm <- nwfscSurvey(common_name = "Sablefish")
gemm_check <- calc_prop_gemm_catch(
data = gemm,
species_name = "Sablefish"
)Visualize the discard length or ages by gear type or catch share vs. non-catch shares:
wcgop_bio <- plot_wcgop_bio(
data = biological_data,
species_name = "Sablefish",
plot = 1:2,
comp_column = "length"
)Once the grouping has been specified, the data are checked to ensure the grouping can meet confidentiality rules. This check based on all the data within the specified grouping, not just the observations of a particular species.
ci <- check_confidential(
data = catch_data,
gear_groups = gear_groups,
gear_names = gear_names,
fleet_colname = fleet_colname,
fleet_groups = fleet_groups,
fleet_names = fleet_names
)The length and or age compositions of discarded fish can be the processed for use in assessment.
bio_data <- get_biological_data(
data = biological_data,
catch_data = catch_data,
species_name = "Sablefish",
len_bins = seq(20, 90, 2),
age_bins = 1:50,
gear_groups = gear_groups,
gear_names = gear_names,
fleet_colname = fleet_colname,
fleet_groups = fleet_groups,
fleet_names = fleet_names
)where the species name, length, and age bins need to be provided.
The mean weight of the discarded fish can also be calculated for using in an assessment:
mean_weight <- get_mean_weights(
data = catch_data,
species_name = "Sablefish",
gear_groups = gear_groups,
gear_names = gear_names,
fleet_colname = fleet_colname,
fleet_groups = fleet_groups,
fleet_names = fleet_names
)The observed catch are then processed for discard rates or totals.
Data from catch share and non-catch share vessels are processed
separately based on attributes of the data. Catch share vessels have 100
percent observer coverage starting in 2011 and are treated as a census
of discarding in the IFQ fishery.
Non-catch share vessels have variable rates of observer coverage and the
discard rates are based on the observed trips. These trips are then
bootstrap to estimate uncertainty around the discard rates.
ob_out <- do_discard_bootstrap(
data = catch_data,
species_name = "Sablefish",
boot_number = 10000,
gear_groups = gear_groups,
gear_names = gear_names,
fleet_colname = fleet_colname,
fleet_groups = fleet_groups,
fleet_names = fleet_names,
seed_number = 1,
rm_em_data = TRUE
)Additionally, a subset of catch share vessels use electronic monitoring (EM) rather that have a physical observer onboard for all trips. These vessels have specific rules about what they can and cannot be discarded at-sea and which species need to be recorded in the logbook and/or monitored by video. The EM program manual can be found online and includes a list of IFQ species. All IFQ species can be discarded at sea within view of cameras. If appropriate, the discard from EM vessels can be processed and are treated as a census of discarding. A subset of trips for vessels that use EM will have a physical onboard observer and be included in the catch records. If EM discards are processed and added to the observed non-EM catch share discards, one must exclude the physical onobard observer data from EM vessels since this would duplicate records.
em_out <- do_discard_bootstrap(
dir = here::here(),
data = em_catch_data,
species_name = "Sablefish",
gear_groups = gear_groups,
gear_names = gear_names,
fleet_colname = fleet_colname,
fleet_groups = fleet_groups,
fleet_names = fleet_names
)The discard rates from the catch share vessels with onboard observers and EM observation can be then combined:
combine_cs_discards(
cs_data = ob_out$cs,
em_data = em_out$em
)